A three-dimensional seepage simulation method for pumped storage power station considering karst development

Abstract

This invention proposes a three-dimensional seepage simulation method for pumped storage power stations considering karst development. The method includes: constructing a comprehensive three-dimensional finite element model encompassing the topography, strata, structure, and key components of the project area; generating random dissolution pores based on geological exploration data that conform to statistical distribution patterns; embedding these pores into the overall model through spatial mapping to form a computational model; assigning permeability parameters and setting seepage boundaries; and finally, numerically solving the three-dimensional seepage field. This invention can accurately characterize random dissolution pores, improve the accuracy and stability of seepage simulation, scientifically assess leakage risks, optimize seepage control schemes, and meet the safety and intelligent construction requirements of pumped storage power station projects in karst areas.

Description

Technical Field

[0001] This invention relates to the field of seepage analysis technology for pumped storage power stations, and in particular to a three-dimensional seepage simulation method for pumped storage power stations that takes karst development into account. Background Technology

[0002] In the construction and operation of pumped storage power stations, seepage analysis in karst areas is a core component for ensuring project safety, assessing leakage risks, and optimizing seepage control schemes. It directly impacts reservoir stability, the safety of underground cavern groups, and water resource utilization efficiency. Three-dimensional finite element simulation of seepage, as a key technology for seepage analysis in karst areas, is widely used in scenarios such as leakage assessment, risk identification, and engineering design optimization in pumped storage power stations. Its simulation accuracy and reliability directly affect the scientific nature of engineering decisions.

[0003] In related technologies, a three-dimensional finite element analysis system for seepage in karst development zones is typically constructed through deterministic modeling or equivalent partitioning. Specifically, this system encompasses the entire process from geological data processing, computational domain construction, parameter assignment to numerical solution, including key steps such as geometric modeling, mesh generation, boundary condition setting, and seepage field calculation. However, existing three-dimensional seepage finite element simulation methods either employ explicit geometric modeling to deterministically characterize exposed dissolution pores or use partitioned homogeneous parameter assignment to equivalently represent the effects of dissolution. These methods fail to achieve accurate characterization and stable coupling of small- to medium-scale random dissolution pores. This can lead to problems such as insufficient model representativeness, mesh modeling failure, and seepage calculation bias. Furthermore, the lack of consideration for the randomness and spatial constraints of dissolution pores can result in misjudgments of leakage risks and insufficient reliability in engineering design, thus affecting the operational safety of pumped storage power stations, the optimization effect of seepage control schemes, and the progress of intelligent construction. Summary of the Invention

[0004] The present invention aims to at least partially solve one of the technical problems in the related art.

[0005] Therefore, the first objective of this invention is to propose a three-dimensional seepage simulation method for pumped storage power stations that takes into account karst development.

[0006] Another objective of this invention is to provide a three-dimensional seepage simulation device for pumped storage power stations that takes into account karst development.

[0007] The third objective of this invention is to provide a computer device.

[0008] A fourth objective of this invention is to provide a non-transitory computer-readable storage medium.

[0009] To achieve the above objectives, a first aspect of the present invention proposes a three-dimensional seepage simulation method for pumped storage power stations considering karst development, comprising:

[0010] S1, construct a comprehensive three-dimensional finite element model covering the topography, strata, structure and hub structure of the engineering area; S2, Based on geological exploration data, extract the statistical distribution law of dissolution pores, and generate random dissolution pores that conform to the statistical distribution law in key areas of soluble strata; S3, embed the random dissolution pores into the overall three-dimensional finite element model through spatial position mapping to form a calculation model containing a set of dissolution pore elements; S4. Assign corresponding permeability parameters to the calculation model and set seepage boundary conditions, perform three-dimensional seepage field numerical solution, and obtain seepage analysis results.

[0011] In one embodiment of the present invention, the construction of a comprehensive three-dimensional finite element model covering the topography, strata, structure, and hub structure of the engineering area includes: Establish a unified three-dimensional coordinate system to clarify the spatial range and outer boundary location of the seepage calculation domain; The lithological zones were divided and key details of the reservoir basin, dam body, underground cavern group, water conveyance system and lining, and drainage holes were included. The grid corresponding to the soluble strata is refined to form a complete computational domain covering the upper reservoir, lower reservoir, surrounding rock, and underground cavern group.

[0012] In one embodiment of the present invention, the step of extracting the statistical distribution law of dissolution pores based on geological exploration data and generating random dissolution pores conforming to the statistical distribution law in key areas of soluble strata includes: Summarize borehole imaging, core logging, and geological exploration data from horizontal tunnel exposure, and extract samples of long axis, medium axis, and short axis scale parameters of dissolution pores, as well as fracture dip and orientation parameters; The parameter samples are subjected to distribution fitting and applicability testing to establish a probability distribution model; Based on the probability distribution model, ellipsoidal dissolution pores are generated by random sampling, and the cumulative dissolution volume and dissolution rate are calculated in real time until the dissolution rate reaches the target value determined by exploration.

[0013] In one embodiment of the present invention, generating random dissolution pores conforming to the statistical distribution law in key areas of the soluble strata includes: The key areas include: the upper warehouse area, the lower warehouse area, and the area surrounding the underground factory building; When generating random dissolution pores, the range of random dissolution pore generation is limited by the lithological constraints of the strata, so that the distribution of dissolution pores conforms to the actual development characteristics of the engineering.

[0014] In one embodiment of the present invention, embedding the random dissolution pores into the overall three-dimensional finite element model through spatial position mapping includes: A spatial geometric equation is constructed based on the center coordinates, scale parameters, and attitude parameters of the random dissolution pores. Analyze the nodal coordinates and centroid coordinates of the soluble strata elements in the overall three-dimensional finite element model; By determining whether the centroid of the unit is within the range defined by the geometric equation, a set of dissolution pore units is formed. The set of dissolved pore elements is written into the finite element model file to achieve coupling with the overall model.

[0015] In one embodiment of the present invention, assigning corresponding permeability parameters to the calculation model and setting seepage boundary conditions includes: The units of different lithological zones are assigned corresponding permeability coefficients, and the dissolution pore unit set is assigned a higher dissolution permeability coefficient than the surrounding rock based on exploration data. The three-dimensional seepage field is numerically solved using pore pressure elements. The seepage analysis results include the seepage pressure field distribution, seepage gradient, flow velocity field, and leakage data.

[0016] In one embodiment of the present invention, the seepage boundary condition includes: The water head boundary and the potential overflow boundary of the cavern are known; The known head boundary causes the pore pressure to be static or piecewise linearly distributed along the elevation. The potential overflow boundary is set on the inner surface of the underground powerhouse and cavern complex, allowing free outflow when the outflow conditions are met, in order to simulate the cavern drainage process.

[0017] To achieve the above objectives, a second aspect of the present invention provides a three-dimensional seepage simulation device for a pumped storage power station considering karst development, comprising: The model building module is used to construct a comprehensive three-dimensional finite element model that covers the topography, strata, structure, and hub structure of the engineering area. The dissolution pore generation module is used to extract the statistical distribution pattern of dissolution pores based on geological exploration data, and generate random dissolution pores that conform to the statistical distribution pattern in key areas of soluble strata. The dissolution pore embedding module is used to embed the random dissolution pores into the overall three-dimensional finite element model through spatial position mapping, forming a computational model containing a set of dissolution pore elements; The seepage solution module is used to assign corresponding seepage parameters to the calculation model and set seepage boundary conditions, perform three-dimensional seepage field numerical solution, and obtain seepage analysis results.

[0018] This invention provides a three-dimensional seepage simulation method and apparatus for pumped storage power stations considering karst development. It enables accurate simulation of the three-dimensional seepage field and scientific assessment of leakage risk in pumped storage power stations in karst development areas, improves model stability and computational efficiency, and fully meets the engineering needs for characterizing the randomness of dissolution pores, accurately capturing seepage patterns, and optimizing seepage control schemes.

[0019] To achieve the above objectives, a third aspect of this application provides a computer device comprising a processor and a memory; wherein the processor runs a program corresponding to the executable program code stored in the memory, for implementing a three-dimensional seepage simulation method for a pumped storage power station considering karst development as described in the first aspect embodiment.

[0020] To achieve the above objectives, the fourth aspect of this application proposes a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements a three-dimensional seepage simulation method for a pumped storage power station considering karst development as described in the first aspect embodiment.

[0021] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0022] Figure 1 This is a flowchart of a three-dimensional seepage simulation method for a pumped storage power station considering karst development, according to an embodiment of the present invention. Figure 2 This is an architectural diagram of a three-dimensional seepage simulation method for a pumped storage power station considering karst development according to an embodiment of the present invention. Figure 3 This is a diagram of the overall three-dimensional seepage finite element calculation model of the engineering area according to an embodiment of the present invention; Figure 4 This is an isodense distribution diagram of crack poles according to an embodiment of the present invention; Figure 5 This is a diagram showing the distribution of random dissolution pores in various parts according to an embodiment of the present invention; Figure 6 This is a distribution diagram of random dissolution pore unit sets in various parts according to an embodiment of the present invention; Figure 7 This is a diagram showing the calculation results of the seepage field in the engineering area under the influence of random dissolution pores according to an embodiment of the present invention; Figure 8 This is a structural diagram of a three-dimensional seepage simulation device for a pumped storage power station considering karst development, according to an embodiment of the present invention. Figure 9 It is a computer device according to an embodiment of the present invention. Detailed Implementation

[0023] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0024] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0025] The following description, with reference to the accompanying drawings, describes a three-dimensional seepage simulation method and apparatus for a pumped storage power station considering karst development, according to an embodiment of the present invention.

[0026] Figure 1 This is a flowchart of a three-dimensional seepage simulation method for a pumped storage power station considering karst development, according to an embodiment of the present invention. Figure 1 and Figure 2 As shown, it includes: S1, construct a comprehensive three-dimensional finite element model covering the topography, strata, structure and hub structure of the engineering area; Specifically, S101: Obtain topographic, stratigraphic, and structural data of the engineering area and the overall layout of the hub, establish a unified three-dimensional coordinate system, and determine the spatial range and outer boundary of the seepage calculation domain.

[0027] S102: Construct a 3D geological model in CAD, including the following: ① Stratigraphic layering: such as the Lower Triassic Feixianguan Formation (T1f), the Lower Triassic Yongningzhen Formation (T1yn), and the first segment of the Middle Triassic Guanling Formation (T2g). 1 ), the second segment of the Guanling Formation in the Middle Triassic (T2g) 1 ); ② Zones of rock mass weathering degree: such as weak upper weathering zone, weak lower weathering zone, and slightly new weathering zone; ③ Main structural features: such as faults.

[0028] S103: Based on the three-dimensional geological model, establish a three-dimensional geometric model of the upper and lower reservoir basins and the dam body, and clarify the key seepage control points such as the bottom of the reservoir basin, the reservoir bank and the dam abutment.

[0029] S104: Establish a three-dimensional geometric model of the underground powerhouse cavern complex and water conveyance system, and incorporate key structural elements such as the lining structure into the model representation.

[0030] S105: In the cavern and tunnel model, drainage structures such as drainage holes are considered as the basis for subsequent seepage boundary setting and drainage process simulation.

[0031] S106: Import the geometric model into HyperMesh for volume mesh generation, and refine the mesh for strata with dissolution conditions to form a complete three-dimensional finite element calculation model covering "upper and lower reservoirs - surrounding rock - underground cavern group", such as Figure 3 The overall dimensions of the computational model are 1535m × 3860m × 777m, and it is divided into 2,682,147 hexahedral solid elements and 484,726 nodes.

[0032] S2, Based on geological exploration data, extract the statistical distribution law of dissolution pores, and generate random dissolution pores that conform to the statistical distribution law in key areas of soluble strata; Specifically, S201: Summarize data such as borehole imaging, core logging, statistical tables of horizontal tunnel structure surfaces, and records of dissolution pore surveys in the engineering area, unify coordinate benchmarks, and complete data cleaning to form a basic database that can be used for statistical analysis.

[0033] S202: Obtain the triaxial length of each dissolved pore from the S201 database: major axis a Central axis b short axis c This forms a sample set.

[0034] in, a i For the first i The major axis parameter of each dissolution pore; b i For the first i The central axis parameters of each dissolution pore; c i For the first i The minor axis parameters of each dissolution pore; N This represents the total number of samples with dissolved pores. i This is the sample index.

[0035] S203: Based on the sample set constructed in S202, the distributions of the three axis lengths are fitted to obtain the probability distribution types and parameters of the three axis lengths:

[0036] in f a , f b , f c The obtained probability density function is the one that is fitted. θ These are the distribution parameters.

[0037] S204: Considering the close relationship between dissolution porosity development and fracture orientation, the azimuth and dip angles of fractures within the dissolution region were statistically analyzed from the S201 database. An isodensity distribution map of the poles was plotted to identify the dominant fracture orientations, and the fractures were grouped according to their dominant orientations. Figure 4 .

[0038] Let the first g The set of fracture samples corresponding to each dominant group is:

[0039] in, S g For the first g A collection of samples showing the orientation of fractures; β i for i The dip azimuth angle of the fracture; γ i For the first i The dip angle of the crack; G This represents the number of dominant fracture groups.

[0040] S205: A collection of fracture orientation samples from different groups constructed based on S204, with the number of samples in each group counted. N g And calculate the percentage of each group:

[0041] in, p g For the first g Percentage of grouped fractures; N g For the first g Number of fracture samples in a group.

[0042] S206: Based on S204 and S205, fit the probability distribution of the tendency and tilt angle for each group, and form a grouped mixed statistical model:

[0043] in,( β,γ ) represents a random vector of fracture orientation; f β,g For the first g Group propensity distribution ；f γ,g For the first g Group tilt angle distribution.

[0044] S207: Use the one-sample KS test to test the fitting results of the major axis length, middle axis length, minor axis length, tendency, and tilt angle to determine the applicability of the statistical models constructed in S203 and S206.

[0045] S208: Compile and output the fracture grouping ratio, the parameters of the occurrence distribution model for each group, and the parameters of the dissolution pore scale distribution model, etc., as input conditions for subsequent Monte Carlo random sampling to generate ellipsoidal random dissolution pores.

[0046] S3, embed the random dissolution pores into the overall three-dimensional finite element model through spatial position mapping to form a calculation model containing a set of dissolution pore elements; Specifically, S301: Select the set of elements that satisfy the properties of soluble strata from the overall finite element model established in S1, and establish three subdomain element sets in HyperMesh: Upper Reservoir Area Ω e,1 Lower Reservoir Area Ω e,2 Ω around the factory e,3 Export the 3D finite element model file model_ini.inp:

[0047] Among them, Ω e,r For the first r A collection of soluble stratigraphic units in key regions; e i Number the units; r =1 indicates the upper storage area. r =2 indicates the lower storage area. r =3 indicates the area surrounding the factory.

[0048] S302: For each region Ω constructed in S301 e,r Based on the barycentric coordinates of this region, its global coordinate range is extracted to define the X-axis coordinates of the ellipsoid center. 0,k Random generation range:

[0049] in, x rmin , x rmax For the first r The area is x Minimum and maximum coordinates of the direction; y rmin , y rmax For the first r The area is y Minimum and maximum coordinates of the direction; z rmin , z rmax For the first r The area is z Minimum and maximum coordinates of the direction.

[0050] S303: In HyperMesh, select the upper reservoir cell set Ω constructed in S301. e,1 Go to the menu Tool→MassCalc; select Elements as the calculation object; the software will automatically perform volume summation on the selected cells to obtain the total volume of the region. V 1; respectively for the lower reservoir area Ω e,2 and the area around the factory Ω e,3 Repeat the above steps to obtain V 2 and V 3.

[0051] S304: Based on the exploration report, determine the measured dissolution rates of the upper and lower storage areas and the areas surrounding the plant, and calculate the target dissolution volume for each area:

[0052] in, V target,r For the first r The target dissolution volume for each region; R r For the first r The dissolution rate was determined through exploration in each area; V r The first calculation for S303 r The total volume of each region.

[0053] S305: Calculate the mean lengths of the three axes to estimate the expected volume of a single ellipsoid, and calculate the initial number of ellipsoids for each region:

[0054] in, a The major axis is the statistical mean; b The mean of the central axis; c E[ is the statistical mean of the minor axis;] ] is the mathematical expectation operator.

[0055] The expected volume of a single ellipsoid is:

[0056] The initial number of ellipsoids for each region is:

[0057] S306: Based on the proportion of cracks in each group in S205, sample the crack group labels:

[0058] in, G r,k For the firstr Region 1 k The fracture group label corresponding to each ellipsoid.

[0059] S307: Based on the fitting results of S203, perform ellipsoidal triaxial length sampling:

[0060] in, a r,k For major axis parameters; b r,k For the central axis parameter; c r,k For minor axis parameters; f a , f b , f c This is the triaxial length probability distribution function obtained by fitting in S203.

[0061] S308: Based on the fitting results of S206, sample the attitude parameters within the group:

[0062] in, β r,k For the first r Region 1 k The azimuth angle of the ellipsoid; γ r,k For the first r Region 1 k The inclination angle of an ellipsoid.

[0063] S309: Based on the statistical results of the S302 range, sample the coordinates of the ellipsoid center:

[0064]

[0065]

[0066] in, U (a,b) Indicates interval [ a , b Uniform distribution on ]; ( x 0,r,k , y 0,r,k , z 0,r,k ) is the first r Region 1 k The coordinates of the center of the ellipsoid.

[0067] S310: Based on the sampling results of the attitude parameters within group S308, the ellipsoidal attitude is constructed and spatially represented, such as... Figure 5 .

[0068] Calculation of major axis:

[0069] Then the major axis unit vector:

[0070] Central axis unit vector:

[0071] Minor axis unit vector:

[0072] S311: Based on the unit vector calculation results of S310, construct the implicit equations of the ellipsoidal space.

[0073] Rotation matrix:

[0074] Scale matrix:

[0075] Ellipsoidal quadratic form matrix:

[0076] S312: Parse the model_ini.inp file exported from S301 to extract the topological and geometric information of each element within the soluble stratum region. Specifically, the model_ini.inp file contains node segments ( NODE, node number and coordinates), unit segment ( ELEMENT, TYPE=C3D4, cell number and its four-node connection relationship), and grouping segment ( ELSET (corresponding to the set of element numbers). Based on the set of regionally soluble strata elements Ω obtained in step S301. e,1 Ω e,2 Ω e,3 Only for Ω e,r Perform geometric calculations and output for each inner element. e i ∈Ω e,r It consists of four nodes, and let the global coordinates of its four nodes be respectively... x i1 , x i2 , x i3 , xi4 .

[0077] Element centroid calculation:

[0078] Among them, X i =[ x i , y i , z i ] is the first i The centroid coordinate vector of each unit; x i1 , x i2 , x i3 , x i4 These are the coordinate vectors of the four nodes of this unit.

[0079] Unit volume calculation:

[0080] in, V i For the first i Unit volume; det[ ] represents determinant operations on a 3×3 matrix; | | represents the absolute value; x i2 - x i1 , x i3 - x i1 , x i4 - x i1 These are the three edge vectors constructed from the node coordinates.

[0081] S313: Collect soluble units from each region Ω e,r Numbering of all units e i , centroid coordinates X i With volume V i Output line by line to Ω e,r The .txt file is output in the following format: ( r , e i , x i , y i , z i ,V i ).

[0082] S314: Read the element centroid and volume data output by S313, and perform ellipsoidal inclusion determination for elements within each region. For any element... e i ∈Ω e,r If there exists the first k An ellipsoid such that:

[0083] Therefore, it is determined that the unit is located inside the dissolution pore:

[0084] in, S r For the first r A collection of regional dissolution porosity units; Ω e,r For the first r A collection of regional soluble stratigraphic units; e i Unit number; X i X represents the coordinates of the unit's centroid; 0,r,k For the first r Region 1 k The coordinates of the center of the ellipsoid; A r,k This is the quadratic form matrix corresponding to the ellipsoid; k This indicates the existence of an ellipsoid such that the discriminant holds.

[0085] S315: Constructed from S314 S r Numbering of all dissolution pore elements within the set e ir , centroid coordinates X ir With volume V ir Output line by line to the Sr.txt file, with the following output format: ( r , e ir , x ir , y ir , z ir , V ir ).

[0086] S316: Calculate the dissolution rate of different regions based on the Sr.txt file output from S315:

[0087]

[0088] in, V diss,r For the first r Volume of regional dissolution pore units; For the first r The dissolution rate is calculated based on the volume of the dissolution pore unit in the region. V r For the first r Total volume of the region.

[0089] S317: Based on the calculated dissolution rate in S317, determine the regional error and convergence:

[0090] in, ε r For the first r Regional dissolution rate error; R r For the first r Regional exploration determines the dissolution rate.

[0091] When a certain area:

[0092] Then the number of ellipsoids in this region will be adjusted:

[0093]

[0094] in, n r For the first r The current number of ellipsoids in the region; Δn r This is the adjustment amount (positive values ​​indicate an increase, negative values ​​indicate a decrease).

[0095] S317: Re-execute steps S307-S317 for this region until the following conditions are met:

[0096] S318: After all three regions meet the convergence condition, the random dissolution porosity elements of the upper storage area, lower storage area, and the area surrounding the factory building are respectively assembled. S r Unit number e i Write the overall 3D model into the model_finall.inp file to form the corresponding group set. ELSET,ELSET=CAVE_SET_r. Figure 6It shows the set of random dissolution pore elements in each region of the overall 3D model.

[0097] S4. Assign corresponding permeability parameters to the calculation model and set seepage boundary conditions, perform three-dimensional seepage field numerical solution, and obtain seepage analysis results.

[0098] S401: Import the finite element model model_finall.inp generated in stage S3 into Abaqus software and establish a steady-state seepage analysis step Soils (Steady-State) to ensure that the finite element model can accurately simulate seepage.

[0099] S402: Assign corresponding permeability coefficients to different stratigraphic zones, and assign dissolution permeability coefficients to dissolution pore unit sets, as shown in Table 1: Table 1

[0100] S403: Based on exploration data, a 709m constant head boundary is applied to the upstream cutoff boundary of the model, and a 246m constant head boundary is applied to the downstream cutoff boundary; a 2m constant head boundary is applied to the bottom and perimeter of the upper reservoir; a 75m constant head boundary is applied to the bottom, perimeter, and upstream face of the dam of the lower reservoir; the bottom of the model is set as an impermeable boundary. The seepage field distribution of the pumped storage engineering area is simulated with the upper reservoir at a dead water level and the lower reservoir at a normal storage water level.

[0101] S404: Defines a keyword in Abaqus to set the downstream face of the dam, the internal surfaces of powerhouses and other caverns as potential overflow boundaries.

[0102] Where Surface set is the name of the set of faces, and QD represents a face. k s This is the free drainage permeability coefficient.

[0103] S405: Abaqus software performs steady-state seepage finite element calculations on the established finite element model based on the applied material parameters and boundary conditions. First, the governing equations are discretized using the finite element discretization method. Then, the elements within the computational domain are assembled to form the overall seepage stiffness matrix, and a global set of finite element equations is established:

[0104] Where: [K] is the overall seepage stiffness matrix; H is the nodal head vector; Q is the nodal seepage boundary flux vector.

[0105] S406: Solve the above equations using a numerical solver to obtain the head value [H] of each element node in the model. Then calculate the seepage pressure field within the model region and output the seepage pressure field distribution results, such as... Figure 7 (a) in the middle.

[0106] S407: Abaqus finite element analysis software uses the built-in flow velocity output variable FLVEL to automatically calculate the seepage velocity vector at each element node, obtaining the flow velocity distribution within the model region, such as... Figure 7 (b) in the middle.

[0107] S408: Using the Abaqus finite element analysis software, the built-in flow output variable RVF was called to statistically calculate the volumetric flow rate at the boundary nodes of the reservoir area under the model, and the leakage rate at each location was obtained by summing the flow rates at the nodes, as shown in Table 2: Table 2

[0108] This invention provides a three-dimensional seepage simulation method for pumped storage power stations considering karst development. Addressing engineering challenges such as the highly random spatial distribution of small-scale dissolution pores in karst-developed areas of pumped storage power stations, the difficulty in deterministic characterization due to limited exploration data, the instability of finite element meshes caused by traditional explicit modeling, and the significant uncertainty in leakage evaluation results, this invention constructs a technical process system comprising "statistical regularity extraction - random dissolution pore generation - finite element mesh mapping and embedding - three-dimensional seepage field simulation and analysis".

[0109] To achieve the above embodiments, such as Figure 8 As shown, this embodiment also provides a three-dimensional seepage simulation device 10 for pumped storage power stations that considers karst development, including: The model building module is used to construct a comprehensive three-dimensional finite element model that covers the topography, strata, structure, and hub structure of the engineering area. The dissolution pore generation module is used to extract the statistical distribution pattern of dissolution pores based on geological exploration data, and generate random dissolution pores that conform to the statistical distribution pattern in key areas of soluble strata. The dissolution pore embedding module is used to embed the random dissolution pores into the overall three-dimensional finite element model through spatial position mapping, forming a computational model containing a set of dissolution pore elements; The seepage solution module is used to assign corresponding seepage parameters to the calculation model and set seepage boundary conditions, perform three-dimensional seepage field numerical solution, and obtain seepage analysis results.

[0110] This invention provides a three-dimensional seepage simulation device for pumped storage power stations that considers karst development. This device enables accurate simulation of the three-dimensional seepage field and scientific assessment of leakage risks in pumped storage power stations located in karst development areas. It improves model stability and computational efficiency, and fully meets the engineering requirements for characterizing the randomness of dissolution pores, accurately capturing seepage patterns, and optimizing seepage control schemes.

[0111] To implement the methods of the above embodiments, the present invention also provides a computer device, such as... Figure 9 As shown, the computer device 600 includes a memory 601 and a processor 602; wherein, the processor 602 reads the executable program code stored in the memory 601 to run a program corresponding to the executable program code, so as to implement the various steps of the three-dimensional seepage simulation method for a pumped storage power station considering karst development described above.

[0112] To implement the above embodiments, this application also proposes a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements a three-dimensional seepage simulation method for a pumped storage power station considering karst development as described in the foregoing embodiments.

[0113] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0114] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

Claims

1. A three-dimensional seepage simulation method for pumped storage power stations considering karst development, characterized in that, include: Construct a comprehensive three-dimensional finite element model covering the topography, strata, structure, and key components of the engineering area; Based on the statistical distribution pattern of dissolution pores extracted from geological exploration data, random dissolution pores conforming to the statistical distribution pattern are generated in key areas of soluble strata. The random dissolution pores are embedded into the overall three-dimensional finite element model through spatial location mapping to form a computational model containing a set of dissolution pore elements; The calculation model is assigned corresponding permeability parameters and permeation boundary conditions are set. The three-dimensional permeation field is numerically solved to obtain the permeation analysis results.

2. The method according to claim 1, characterized in that, The construction of the overall three-dimensional finite element model, encompassing the topography, strata, structure, and key features of the engineering area, includes: Establish a unified three-dimensional coordinate system to clarify the spatial range and outer boundary location of the seepage calculation domain; The lithological zones were divided and key details of the reservoir basin, dam body, underground cavern group, water conveyance system and lining, and drainage holes were included. The grid corresponding to the soluble strata is refined to form a complete computational domain covering the upper reservoir, lower reservoir, surrounding rock, and underground cavern group.

3. The method according to claim 1, characterized in that, The method of extracting the statistical distribution pattern of dissolution pores based on geological exploration data, and generating random dissolution pores conforming to the statistical distribution pattern in key areas of soluble strata, includes: Summarize borehole imaging, core logging, and geological exploration data from horizontal tunnel exposure, and extract samples of long axis, medium axis, and short axis scale parameters of dissolution pores, as well as fracture dip and orientation parameters; The parameter samples are subjected to distribution fitting and applicability testing to establish a probability distribution model; Based on the probability distribution model, ellipsoidal dissolution pores are generated by random sampling, and the cumulative dissolution volume and dissolution rate are calculated in real time until the dissolution rate reaches the target value determined by exploration.

4. The method according to claim 1, characterized in that, The generation of random dissolution pores conforming to the statistical distribution law in key areas of soluble strata includes: The key areas include: the upper warehouse area, the lower warehouse area, and the area surrounding the underground factory building; When generating random dissolution pores, the range of random dissolution pore generation is limited by the lithological constraints of the strata, so that the distribution of dissolution pores conforms to the actual development characteristics of the engineering.

5. The method according to claim 1, characterized in that, The step of embedding the random dissolution pores into the overall three-dimensional finite element model through spatial location mapping includes: A spatial geometric equation is constructed based on the center coordinates, scale parameters, and attitude parameters of the random dissolution pores. Analyze the nodal coordinates and centroid coordinates of the soluble strata elements in the overall three-dimensional finite element model; By determining whether the centroid of the unit is within the range defined by the geometric equation, a set of dissolution pore units is formed. The set of dissolved pore elements is written into the finite element model file to achieve coupling with the overall model.

6. The method according to claim 1, characterized in that, Assigning corresponding permeability parameters to the calculation model and setting seepage boundary conditions includes: The units of different lithological zones are assigned corresponding permeability coefficients, and the dissolution pore unit set is assigned a higher dissolution permeability coefficient than the surrounding rock based on exploration data. The three-dimensional seepage field is numerically solved using pore pressure elements. The seepage analysis results include the seepage pressure field distribution, seepage gradient, flow velocity field, and leakage data.

7. The method according to claim 1, characterized in that, The seepage boundary conditions include: The water head boundary and the potential overflow boundary of the cavern are known; The known head boundary causes the pore pressure to be static or piecewise linearly distributed along the elevation. The potential overflow boundary is set on the inner surface of the underground powerhouse and cavern complex, allowing free outflow when the outflow conditions are met, in order to simulate the cavern drainage process.

8. A three-dimensional seepage simulation device for pumped storage power stations considering karst development, characterized in that, include: The model building module is used to construct a comprehensive three-dimensional finite element model that covers the topography, strata, structure, and hub structure of the engineering area. The dissolution pore generation module is used to extract the statistical distribution pattern of dissolution pores based on geological exploration data, and generate random dissolution pores that conform to the statistical distribution pattern in key areas of soluble strata. The dissolution pore embedding module is used to embed the random dissolution pores into the overall three-dimensional finite element model through spatial position mapping, forming a computational model containing a set of dissolution pore elements; The seepage solution module is used to assign corresponding seepage parameters to the calculation model and set seepage boundary conditions, perform three-dimensional seepage field numerical solution, and obtain seepage analysis results.

9. A computer device, characterized in that, Including processor and memory; The processor reads executable program code stored in the memory to run a program corresponding to the executable program code, so as to implement a three-dimensional seepage simulation method for pumped storage power stations considering karst development as described in any one of claims 1-7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements a three-dimensional seepage simulation method for a pumped storage power station considering karst development as described in any one of claims 1-7.

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